Abstract
Objective
This study aims to explore the relationship between daily sedentary time (ST) and the risk of polyvascular disease (PVD) in older adults, as well as to assess the influence of physical activity on this association.
Methods
This cross-sectional analysis utilizes baseline data from the Polyvascular Evaluation for Cognitive Impairment and Vascular Events (PRECISE), a population-based prospective cohort involving 3067 community-dwelling adults aged 50-75. Daily ST and moderate- to vigorous-intensity physical activity (MVPA) were categorized into tertiles. Polyvascular lesions in major arteries were examined using computed tomography angiography (CTA) and magnetic resonance imaging (MRI). PVD was defined as the simultaneous presence of atherosclerotic plaque or stenosis in at least two major vascular territories. Binary regression models were employed to evaluate the associations between daily ST and PVD risk, as well as the moderating effect of MVPA.
Results
Two thousand five hundred forty-one (82.8%) participants had atherosclerotic plaques and 412 (13.4%) participants had atherosclerotic stenosis in at least two vascular territories. Daily ST was significantly associated with an increased risk of multi-vessel atherosclerotic plaques, with this association remaining robust even after adjusting for potential confounders [OR (Ts3 vs Ts1), 1.77; 95%CI, 1.30-2.42]. The association between daily ST and multi-vessel atherosclerotic stenosis was not observed. Among different arterial territories, daily ST was associated with risk of plaque formation in extracranial [OR (Ts3 vs Ts1), 1.29; 95%CI, 1.00-1.65; p=0.047] and Ilio-femoral [OR (Ts3 vs Ts1), 1.43; 95%CI, 1.08-1.90; p=0.01] arteries, and was significantly associated with the risk of both atherosclerotic plaque [OR (Ts3 vs Ts1), 1.47; 95%CI, 1.09-1.96; p=0.01] and luminal stenosis [OR (Ts3 vs Ts1), 2.06; 95%CI, 1.03-4.11; p=0.04] in renal artery. Notably, the association between prolonged ST and multi-vessel atherosclerotic plaques persisted even among participants with the highest levels of MVPA, indicating that the benefits of physical activity may not fully offset the risks of excessive sitting.
Conclusion
Prolonged daily ST acts as an independent risk factor for multi-vessel atherosclerotic plaques that is not completely reversible by physical activity, underscoring the importance of reducing sitting time regardless of exercise levels. Three arterial territories were affected by atherosclerosis associated with sedentary behavior, the extracranial, iliofemoral, and renal arteries.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12889-026-26549-4.
Keywords: Sedentary time, Moderate- to vigorous-intensity physical activity, Polyvascular disease
Introduction
The high prevalence of sedentary behavior has become a significant public health concern. Sedentary behavior is well-established as being associated with increased cardiovascular and all-cause mortality [1–4], particularly in older adults who engage in high volumes of sedentary activities and have comorbidities. Recent large-scale prospective cohort studies [5, 6] have demonstrated that prolonged sedentary time (ST) is linked to higher risks of ischemic heart disease and stroke.
Behavioral interventions, particularly physical activity (PA), are widely recognized for their cardiovascular benefits [7, 8]. Although sedentary behavior and MVPA are independent behaviors that can coexist in the same individual, previous studies have suggested that high levels of MVPA may attenuate some cardiovascular risks associated with prolonged sedentary time [4]. Mechanistically, MVPA promotes laminar shear stress and metabolic regulation, which may counteract the endothelial dysfunction and systemic inflammation induced by prolonged inactivity. Nevertheless, different studies have indicated inconsistent outcomes regarding whether and how MVPA levels modify the relationship between ST and adverse health outcomes.
Moreover, polyvascular disease (PVD) has gained increasing attention in recent years. According to the European Society Cardiology Guidelines, PVD is defined as the simultaneous presence of “clinically significant” atherosclerotic plaques in at least two major vascular territories [9]. Traditionally, coronary heart disease, cerebrovascular disease, and peripheral artery disease (PAD) have been studied separately despite sharing similar pathophysiological mechanisms and risk factors. Recently, however, researchers have gradually shifted their focus from mono-vascular disease to PVD, which affect multiple vascular territories throughout the body.
Accumulating evidence suggests that PVD increases the incidence of cardiovascular events [10–13]. According to the earlier CRUSADE (Can Rapid risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the ACC/AHA guidelines) [14] initiative, patients with acute coronary syndromes and concomitant peripheral artery disease—indicating polyvascular involvement—faced significantly worse clinical outcomes and higher mortality. Similarly, the more recent EXSCEL (Exenatide Study of Cardiovascular Event Lowering) trial [15] showed that among patients with type 2 diabetes, adverse cardiovascular events increased incrementally as additional diseased arterial territories were identified. Furthermore, the results of the REACH (Reduction of Atherothrombosis for Continued Health) registry [16], involving more than 60,000 subjects, demonstrated that polyvascular disease was a strong predictor of ischemic major adverse cardiovascular events (MACE) over a four-year period, with associated risks exceeding those of single-bed disease or diabetes alone.
Therefore, it would not be unreasonable to speculate that sedentary behavior could be associated with PVD. In the present study, we analyzed the baseline data from the Polyvascular Evaluation for Cognitive Impairment and Vascular Events (PRECISE) study (June 4, 2017 ClinicalTrials. gov Registry: NCT03178448) [17, 18], examined atherosclerotic lesions in the major arteries throughout the body using imaging of computed tomography angiography (CTA) or magnetic resonance imaging (MRI), and evaluated the association between daily ST and PVD risk and the effect of MVPA on this relationship.
Methods
Study design
This cross-sectional analysis uses baseline data from the Polyvascular Evaluation for Cognitive Impairment and Vascular Events (PRECISE) study, an ongoing population-based prospective cohort. PRECISE aims to comprehensively assess the prevalence and progression of atherosclerotic lesions in multiple vascular territories and the association of polyvascular lesions with future cognitive impairment and cardiovascular risk in community-dwelling older adults in China. Between May 2017 and September 2019, totally 3067 community-dwelling adults aged 50–75 years from 6 villages and 4 communities in Lishui, southeastern China, were enrolled into the study and then entered a 4-year follow-up period after baseline data collection. Participants were scheduled to undergo face-to-face interviews at 2- and 4-year follow-up visits. Information on vascular risk factors, medication use, deaths, cardiovascular events, systemic embolism, and endovascular procedures during the follow-up period would be collected. Assessment of atherosclerotic lesions of major arterial vessels throughout the body was planned to be performed at baseline and at the 4-year follow-up visit. We performed a vascular MRI to examine the intracranial and extracranial arteries, thoracoabdominal CTA to examine the coronary, subclavian, aorta, renal, and iliofemoral arteries, and ankle-arm index (ABI) to evaluate peripheral vessels. All participants provided written informed consent, and their data were used exclusively for research purposes, ensuring strict confidentiality.
Inclusion and exclusion criteria
Participants were included if they were community-dwelling adults aged 50–75 years, residents of Lishui, southeastern China, and willing to participate and provide informed consent. Exclusion criteria included severe comorbid conditions such as advanced cancer or end-stage renal disease, cognitive impairment affecting the ability to provide informed consent, and mobility issues preventing participation in follow-up assessments [19].
Polyvascular disease
Previous studies have defined PVD relying on either an established medical history of coronary artery disease, cerebrovascular disease, and PAD, or a crude assessment by vascular ultrasound of arterial vascular sites. This can lead to misjudgments, for instance, a diagnosis of coronary artery disease based solely on ambiguous history, without objective, gold-standard findings such as coronary CTA or coronary angiography [16]. Some other studies have only assessed the local vascular beds but have not performed a comprehensive evaluation of atherosclerotic lesions in multiple vascular territories. Incomplete or crude examinations of the arterial system can make the assessment of PVD unreliable. To facilitate description, the present study provides an unambiguous definition of PVD [20]. We have classified the primary arterial system into the following vascular territories: ①intracranial artery,②extracranial artery, ③coronary artery, ④subclavian artery, ⑤aorta, ⑥renal artery, ⑦iliac and femoral artery, and ⑧peripheral artery. Assessment was territory-specific: (1) For the intracranial, extracranial, coronary, subclavian, aortic, renal, and iliofemoral arteries, lesions were identified using MRI or CTA and defined as atherosclerotic plaque (<50% luminal stenosis) or atherosclerotic stenosis (≥50% luminal stenosis). (2) For the distal peripheral arteries, considering the feasibility of assessment, we employed ABI instead of CTA, with a value of ≤0.9 confirming the presence of lesions. PVD was defined as the simultaneous involvement of at least two territories confirmed by these respective methods.
Sedentary time and physical activity
Daily ST and PA were self-reported and collected using a questionnaire in which the categories of PA were modified based on the International Physical Activity Questionnaire (IPAQ) [21]. Detailed information are available in supplementary material online. The daily ST refers to the average time spent sitting or lying at work, studying, reading, watching television, using the computer, driving, resting, etc. on a typical day during the last year. Sleep time, however, was not included in the calculation.
PA was assessed by the value of metabolic equivalent of task (MET)-hour/week. As a reference, one MET was defined as the energy expenditure while sitting quietly for one hour. The MET value for a particular category of PA was expressed as the ratio of the work metabolic expenditure to a standard resting metabolic expenditure [21]. We referred to the Physical Activity Compendium 2011 and supplementary information [24] for MET values for different types of PA, estimating a MET value of 4.0 for moderate-intensity activity (MPA) and 8.0 for vigorous-intensity activity (VPA) as an average value [21]. For each participants, we collected the amount of time spent per week engaged in MPA and VPA respectively, calculated the intensity-specific MET-hour/week as the product of the average MET value and the numbers of MPA/VPA hours in a typical week, and summed up the intensity-specific MET-hour/week to produce the total MET-hour/week for MVPA (as a reference, 7.5 MET-hr/week equivalent to 150 min/week of moderate-intensity physical activity [25, 26]). All interviewers received centralized training prior to the kick-off meeting. Upon approval of the Steering Committee, a standard data collection protocol was followed in conducting interviews.
Intracranial and extracranial vascular MRI
The intracranial and extracranial arteries were evaluated using a 3.0 T MRI scanner (Ingenia 3.0 T [Philips]). MRI sequences included three-dimensional time-of-flight magnetic resonance angiography (3-D-TOF MRA), three-dimensional isotropic high-resolution black-blood T1w vessel wall imaging, and simultaneous non-contrast angiography and intraplaque hemorrhage imaging. Atherosclerotic plaques of cerebral arteries were defined as eccentric wall thickening with less than 50% luminal stenosis shown on 3-D-TOF MRA or black blood MRI images. Intracranial and extracranial arterial stenosis was defined as 50% to 99% luminal stenosis [7].
Thoracoabdominal CTA
CTA images of coronary, subclavian, aorta, renal, and iliofemoral arteries were acquired at baseline using a dual-source CT scanner (SOMATOM Force [Siemens]). The CTA images were interpreted by 2 raters, who were masked to the information of the enrolled subjects, from the cardiac image viewing workstation of the Core Imaging Laboratory of Keya Medical Technology (Shenzhen, China). Automated geometric 3D reconstruction of CTA images was performed using a multi-task deep learning network for qualitative and quantitative analysis of plaques and stenoses. Atherosclerotic lesions were determined by experienced imaging analysts based on the CTA images and quantitative analysis. Atherosclerotic plaques were defined as any structures that were at least one millimeter in size and could be clearly distinguished from the arterial lumen [27]. For each region of vascular beds, the degree of stenosis was measured as the most severely stenotic plaque. The presence of stenosis in the aforementioned territories of vascular beds was defined as luminal stenosis of 50% to 99%.
ABI
This study used ABI to assess clinically significant atherosclerosis in peripheral arteries. ABI was determined using Doppler ultrasound (Huntleigh Health Care Ltd), and it was defined as abnormal if the ABI value was less than or equal to 0.9.
Covariates
We collected information on age, sex, education, smoking, salt intake, psychological stress, and the history of hypertension, diabetes, dyslipidemia, coronary heart disease, and stroke/transient ischemic attacks (TIA) through the questionnaire. The height (m) and weight (kg) of participants were measured separately using a tape and a calibrated weight scale, and body mass index (BMI) values were obtained based on the following formula: BMI=weight (kg)/height (m)2. Blood pressure was measured by auscultation with a mercury sphygmomanometer after the participants had been sitting still for more than 20 minutes, and the mean value was taken after two measurements. Fasting blood samples were collected from participants and subsequently tested for levels of glycated hemoglobin (HbA1c) and low-density lipoprotein cholesterol (LDL-C) at the Lishui People's Hospital.
Data quality control and image analysis
To ensure data consistency, all interviewers underwent centralized training and performance assessment prior to the study. An Electronic Data Capture (EDC) system with automatic logic verification was used for questionnaire data collection. For the assessment of PVD, all vascular images (MRI and CTA) were analyzed by a Central Core Laboratory. Images were interpreted by two independent specialists blinded to clinical details, with discrepancies resolved by a third senior reader to ensure high inter-observer agreement.
Statistical analysis
Socio-demographic and clinical characteristics were described as mean values (with standard deviations) or percentages across tertiles of daily ST. Differences across tertiles were tested using One-Way ANOVA or Kruskal-Wallis test for continuous variables and Chi-Squared test for categorical variables. We estimated the association of daily ST with PVD risk by binary logistic regression with odds ratios (OR) and their 95% confidence intervals (CIs). Three regression models were used to analyze the association of interest. Model 1 was adjusted for age and sex. Model 2 additionally included the adjustment of potential confounders of current smoking status, current drinking status, BMI, hypertension, diabetes, and dyslipidemia. Model 3 added the physiological and biochemical indices of systolic blood pressure (SBP), HbA1c and LDL-C to model 2. Model 1, 2, 3 were also used to examine the association of daily ST with the presence of atherosclerotic plaques/stenoses in a particular arterial territories. Moreover, we investigated the potential impact of tertiles of MVPA, which was considered as a confounder or a competing behavior, on the association between sedentary behavior and incidence of PVD. The reference group was the population with the highest tertile of MVPA (Ta3) and the lowest tertile of daily ST (Ts1). That is, we examined separately whether there were differences in the relationship between daily ST and PVD in each MVPA stratum. Missing data from vascular imaging were not recorded, but eligible image data were included in the analysis. Statistical significance for all analyses was defined as p < 0.05. All the statistical analyses were conducted with SAS version 9.4 (SAS Institute Inc.) for Windows.
Results
Participant demographics and baseline characteristics
A total of 3067 subjects were included in baseline data collection for the PRECISE study. All of these participants had available imaging data in at least one vascular site and were therefore enrolled in the study. The baseline characteristics of the participants were shown in Table 1. The participants with longer ST were more likely to be well educated, to have higher rates of comorbid diabetes and dyslipidemia, but to be relatively less psychologically stressed. The mean ST (SD) in tertiles1, 2 and 3 were 1.0 (0.3), 2.5 (0.5) and 5.8 (1.9) h/day, respectively. Participants with longer ST also, unsurprisingly, had lower levels of MVPA [27.2±21.1 (Ts1), 24.1±16.6 (Ts2), 13.8±10.6 (Ts3), p<0.001]. There were 2541 (82.8%) and 412 (13.4%) patients with arterial atherosclerotic plaques and stenotic lesions in two or more vascular territories, respectively. With increasing tertiles of daily ST, the percentage of patients with either multi-vessel plaques increased significantly (p<0.001).
Table 1.
Baseline characteristics, stratified by tertiles of daily sedentary time (n=3067): PRECISE (2017-2019)
| Characteristics | Daily Sedentary Time Tertiles a | P | ||
|---|---|---|---|---|
| Ts1 (low) | Ts2 | Ts3 (high) | ||
| N (%) | 397 (12.9) | 1455 (47.5) | 1215 (39.6) | |
| Age, mean (SD) | 60.4±6.6 | 61.4±6.6 | 61.2±6.8 | 0.04 |
| Sex, n (%) | <0.001 | |||
| Men | 150(37.8) | 664(45.6) | 613(50.5) | |
| Women | 247(62.2) | 791(54.4) | 602(49.5) | |
| Education, n (%) | <0.001 | |||
| <High school | 325(81.9) | 1151(79.1) | 819(67.4) | |
| ≥ High school | 72(18.1) | 304(20.9) | 396(32.6) | |
| Current smoking, n (%) | 65(16.4) | 294(20.2) | 270(22.2) | 0.04 |
| Daily salt intake, n (%) | 0.20 | |||
| <6g | 155(39.0) | 493(33.9) | 406(33.4) | |
| 6-12g | 153(38.5) | 605(41.6) | 531(43.7) | |
| >12g | 89(22.4) | 357(24.5) | 278(22.9) | |
| psychological stress, n (%) | 54(13.6) | 121(8.3) | 101(8.3) | <0.001 |
| BMI (kg/m2), mean (SD) | 23.5±2.9 | 23.8±3.0 | 23.8±3.1 | 0.19 |
| Hypertension, n (%) | 166(41.8) | 610(41.9) | 545(44.9) | 0.27 |
| Diabetes, n (%) | 64(16.1) | 309(21.2) | 290(23.9) | 0.004 |
| Dyslipidemia, n (%) | 66(16.6) | 277(19.0) | 273(22.5) | 0.02 |
| Coronary heart disease, n (%) | 0(0.0) | 7(0.5) | 6(0.5) | 0.38 |
| Ischemic stroke/TIA, n (%) | 13(3.3) | 29(2.0) | 45(3.7) | 0.03 |
| Systolic blood pressure (mmHg), mean (SD) | 129.0±16.3 | 129.6±16.3 | 129.0±16.4 | 0.58 |
| Diastolic blood pressure (mmHg), mean (SD) | 74.7±8.9 | 75.3±9.1 | 75.3±9.0 | 0.47 |
| HbA1c, mean (SD) | 5.9±0.7 | 5.9±0.9 | 6.0±1.0 | 0.22 |
| LDL-C, mg/dl, mean (SD) | 2.8±0.9 | 2.8±0.8 | 2.8±0.8 | 0.87 |
| Daily sedentary time (hour/day), mean (SD) | 1.0±0.3 | 2.5±0.5 | 5.8±1.9 | <0.001 |
| MVPA (MET-h/week), mean (SD) | 27.2±21.1 | 24.1±16.6 | 13.8±10.6 | <0.001 |
| Presence of AP in at least 2 major vascular territories, n (%) | 293(73.8) | 1211(83.2) | 1037(85.4) | <0.001 |
| Presence of AS in at least 2 major vascular territories, n (%) | 41(10.3) | 194(13.3) | 177(14.6) | 0.10 |
Abbreviations: BMI body mass index, TIA transient ischemic attacks, HbA1c haemoglobin A1c, LDL-C low-density lipoprotein cholesterol, MVPA moderate- to vigorous-intensity physical activity, AP atherosclerotic plaque, AS atherosclerotic stenosis
aTertile (Ts) ranges of daily sedentary time (hours/day): 0≤Ts1<2, 2≤Ts2<4, Ts3≥4
Increased risk of multi-vessel atherosclerotic plaques with higher sedentary time
An association between daily ST and multi-vessel atherosclerotic plaques was easily observed (Table 2). Representative CTA images illustrating multi-vessel atherosclerotic lesions, including those in the abdominal aorta, are presented in Supplementary Figure 1. After adjusting for age and sex (Model 1), the odds of atherosclerotic plaque [OR (Ts3 vs Ts1), 1.82; 95%CI, 1.36–2.44.36.44] were progressively higher over increasing tertiles of daily ST. After adjusting for the potential confounders (Model 2), the association was not attenuated but remained statistically significant [OR (Ts3 vs Ts1), 1.75; 95%CI, 1.29–2.37.29.37]. For further adjustment, relevant physiological and biochemical parameters were sequentially added to the regression model (Model 3), and the association persisted and the ORs did not change much [OR (Ts3 vs Ts1), 1.77; 95%CI, 1.30–2.42.30.42]. However, similar association was not found between daily ST and multi-vessel atherosclerotic stenosis. Across all models, there were no statistically significant differences in the odds of multi-vessel stenosis among the different tertiles of daily ST, indicating that prolonged sedentary behavior may not be a contributing factor to atherosclerotic stenosis in multiple vascular territories. Sensitivity analyses using quartiles of daily ST yielded consistent results, confirming the significant association with atherosclerotic plaques and the lack of association with atherosclerotic stenosis (Supplementary Table 1).
Table 2.
Association between categories of daily sedentary time a and risk of polyvascular diseaseb
| N (%) | Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|---|
| adjusted OR (95%CI) | Pc | adjusted OR (95%CI) | Pc | adjusted OR (95%CI) | Pc | ||
| Atherosclerotic plaque b | |||||||
| Ts1 | 293 (73.8) | 1 (ref) | 1 (ref) | 1 (ref) | |||
| Ts2 | 1211 (83.2) | 1.56(1.17–2.06.17.06) | 0.002 | 1,53(1.14–2.04.14.04) | 0.005 | 1.53(1.14–2.06.14.06) | 0.005 |
| Ts3 | 1037 (85.3) | 1.82(1.36–2.44.36.44) | <0.001 | 1.75(1.29–2.37.29.37) | <0.001 | 1.77(1.30–2.42.30.42) | <0.001 |
| Atherosclerotic stenosis b | |||||||
| Ts1 | 41 (10.3) | 1 (ref) | 1 (ref) | 1 (ref) | |||
| Ts2 | 194 (13.3) | 1.18(0.82–1.71.82.71) | 0.38 | 1.17(0.80–1.71.80.71) | 0.43 | 1.18(0.80–1.74.80.74) | 0.40 |
| Ts3 | 177 (14.6) | 1.29(0.89–1.88.89.88) | 0.18 | 1.19(0.81–1.75.81.75) | 0.38 | 1.23(0.84–1.83.84.83) | 0.29 |
The reference group was defined as the lower tertile of daily sedentary time (Ts1)
Abbreviations: OR odds ratio, CI confidence interval
aTertile (Ts) ranges of daily sedentary time (hours/day): 0≤Ts1<2, 2≤Ts2<4, Ts3≥4
b ≥2 arterial territories affected with atherosclerosis (atherosclerotic plaque/stenosis)
cP-values from binary logistic regression models with daily sedentary time as independent variable
Model 1: Adjusted for age and sex.
Model 2: model 1 + current smoking status, current drinking status, BMI, hypertension, diabetes, and dyslipidemia.
Model 3: model 2 + systolic blood pressure, HbA1c, LDL-C
We further performed a subgroup analysis stratified by standard modifiable cardiovascular risk factors (SMuRFs), including diabetes, hypertension, dyslipidemia, and current smoking status. We observed a significant interaction between hypertension and sedentary time for the risk of atherosclerotic stenosis (Pinteraction=0.002), where the association was significant in hypertensive patients (OR=1.09, 95% CI: 1.03–1.16.03.16) but not in non-hypertensive individuals. No significant interactions were observed for diabetes, dyslipidemia, or smoking status, nor for the outcome of atherosclerotic plaque (Supplementary Table 3).
Differential impact of sedentary time on specific arterial territories
Among different arterial territories, daily ST was associated with risk of plaque formation in extracranial, renal, and Ilio-femoral arteries (Table 3). Participants in tertile 3 of daily ST had a 31%, 53%, and 44% higher risk of atherosclerotic plaques in extracranial, renal, and ilio-femoral arteries as compared with tertile 1 (Model 3). The association of daily ST with risk of arterial stenotic lesions could only be observed in renal artery (Model 1, p=0.03; Model 2, p=0.04; Model 3, p=0.03). Notably, daily ST was significantly associated with the risk of both atherosclerotic plaque and luminal stenosis in renal artery.
Table 3.
Association between categories of daily sedentary time and arterial territories with atherosclerotic plaque and stenosis
| Daily Sedentary Time Tertiles¶ | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Atherosclerotic plaque | Atherosclerotic stenosis | |||||||||||||
| Model 1 | Model 2 | Model 3 | Model 1 | Model 2 | Model 3 | |||||||||
| Group | N(%) | Adjusted OR (95%CI) | P ∮ | Adjusted OR (95%CI) | P ∮ | Adjusted OR (95%CI) | P ∮ | N(%) | Adjusted OR (95%CI) | P ∮ | Adjusted OR (95%CI) | P ∮ | Adjusted OR (95%CI) | P ∮ |
| Intracranial artery§ | ||||||||||||||
| Ts1 | 60(15.1) | ref | ref | ref | 14(3.5) | ref | ref | ref | ||||||
| Ts2 | 275(18.9) | 1.24(0.91–1.69.91.69) | 0.17 | 1.22(0.89–1.67.89.67) | 0.22 | 1.23(0.89–1.69.89.69) | 0.21 | 74(5.1) | 1.38(0.77–2.48.77.48) | 0.28 | 1.35(0.75–2.44.75.44) | 0.32 | 1.35(0.74–2.44.74.44) | 0.64 |
| Ts3 | 207(17.0) | 1.09(0.79–1.50.79.50) | 0.59 | 1.01(0.73–1.40.73.40) | 0.94 | 1.05(0.75–1.45.75.45) | 0.79 | 55(4.5) | 1.22(0.67–2.24.67.24) | 0.51 | 1.13(0.61–2.07.61.07 | 0.7 | 1.16(0.63–2.13.63.13) | <0.001 |
| Extracranial artery§ | ||||||||||||||
| Ts1 | 120(30.3) | ref | ref | ref | 4(1.0) | ref | ref | ref | ||||||
| Ts2 | 533(36.9) | 1.27(1.00–1.62.00.62) | 0.053 | 1.26(0.99–1.61.99.61) | 0.059 | 1.28(1.00–1.63.00.63) | 0.051 | 12(0.8) | 0.72(0.23–2.25.23.25) | 0.57 | 0.64(0.20–2.02.20.02) | 0.44 | 0.63(0.20–2.02.20.02) | 0.44 |
| Ts3 | 457(37.9) | 1.30(1.02–1.67.02.67) | 0.04 | 1.29(1.00–1.65.00.65) | 0.047 | 1.31(1.02–1.68.02.68) | 0.03 | 17(1.4) | 1.19(0.39–3.57.39.57) | 0.76 | 0.95(0.31–2.90.31.90) | 0.92 | 0.99(0.32–3.06.32.06) | 0.99 |
| Coronary artery§ | ||||||||||||||
| Ts1 | 160(40.5) | ref | ref | ref | 58(14.7) | ref | ref | ref | ||||||
| Ts2 | 644(44.6) | 1.06(0.83–1.34.83.34) | 0.65 | 1.02(0.80–1.30.80.30) | 0.86 | 1.03(0.81–1.31.81.31) | 0.82 | 247(17.1) | 1.09(0.79–1.50.79.50) | 0.59 | 1.07(0.77–1.47.77.47) | 0.69 | 1.07(0.77–1.47.77.47) | 0.70 |
| Ts3 | 562(46.6) | 1.14(0.90–1.46.90.46) | 0.28 | 1.07(0.84–1.37.84.37) | 0.59 | 1.08(0.84–1.39.84.39) | 0.54 | 237(19.7) | 1.29(0.94–1.78.94.78) | 0.12 | 1.22(0.88–1.69.88.69) | 0.22 | 1.23(0.89–1.70.89.70) | 0.21 |
| Subclavian artery§ | ||||||||||||||
| Ts1 | 166(42.7) | ref | ref | ref | 33(8.5) | ref | ref | ref | ||||||
| Ts2 | 734(51.3) | 1.30(1.02–1.65.02.65) | 0.03 | 1.27(1.00–1.62.00.62) | 0.054 | 1.28(1.00–1.64.00.64) | 0.051 | 137(9.6) | 1.07(0.72–1.61.72.61) | 0.73 | 1.06(0.71–1.59.71.59) | 0.78 | 1.08(0.72–1.63.72.63) | 0.70 |
| Ts3 | 600(50.4) | 1.24(0.97–1.59.97.59) | 0.08 | 1.18(0.91–1.51.91.51) | 0.21 | 1.20(0.93–1.54.93.54) | 0.16 | 138(11.6) | 1.34(0.89–2.01.89.01) | 0.15 | 1.32(0.88–1.98.88.98) | 0.18 | 1.37(0.91–2.07.91.07) | 0.13 |
| Aortic artery§ | ||||||||||||||
| Ts1 | 289(73.5) | ref | ref | ref | 9(2.3) | ref | ref | ref | ||||||
| Ts2 | 1147(79.5) | 1.22(0.92–1.60.92.60) | 0.16 | 1.18(0.89–1.56.89.56) | 0.26 | 1.18(0.89–1.57.89.57) | 0.25 | 26(1.8) | 0.68(0.31–1.47.31.47) | 0.33 | 0.68(0.31–1.49.31.49) | 0.34 | 0.71(0.32–1.57.32.57) | 0.40 |
| Ts3 | 983(81.7) | 1.39(1.05–1.84.05.84) | 0.02 | 1.32(0.98–1.77.98.77) | 0.06 | 1.33(0.99–1.79.99.79) | 0.057 | 30(2.5) | 0.92(0.43–1.98.43.98) | 0.84 | 0.84(0.39–1.82.39.82) | 0.66 | 0.91(0.42–2.00.42.00) | 0.82 |
| Renal artery § | ||||||||||||||
| Ts1 | 88(22.3) | ref | ref | ref | 10(2.5) | ref | ref | ref | ||||||
| Ts2 | 414(28.7) | 1.33(1.00–1.75.00.75) | 0.047 | 1.33(1.00–1.78.00.78) | 0.05 | 1.36(1.01–1.82.01.82) | 0.04 | 64(4.4) | 1.59(0.80–3.15.80.15) | 0.18 | 1.63(0.82–3.26.82.26) | 0.17 | 1.70(0.85–3.42.85.42 | 0.14 |
| Ts3 | 371(30.8) | 1.51(1.14–2.01.14.01) | 0.004 | 1.47(1.09–1.96.09.96) | 0.01 | 1.53(1.14–2.06.14.06) | 0.005 | 71(5.9) | 2.12(1.07–4.18.07.18) | 0.03 | 2.06(1.03–4.11.03.11) | 0.04 | 2.21(1.10–4.44.10.44) | 0.03 |
| Ilio-femoral artery § | ||||||||||||||
| Ts1 | 266(67.3) | ref | ref | ref | 62(15.7) | ref | ref | ref | ||||||
| Ts2 | 1098(75.8) | 1.31(1.01–1.71.01.71) | 0.04 | 1.27(0.97–1.67.97.67) | 0.09 | 1.27(0.96–1.68.96.68) | 0.09 | 234(16.2) | 0.87(0.63–1.20.63.20) | 0.41 | 0.82(0.59–1.15.59.15) | 0.25 | 0.83(0.59–1.16.59.16) | 0.26 |
| Ts3 | 948(78.5) | 1.52(1.16–2.00.16.00) | 0.003 | 1.43(1.08–1.90.08.90) | 0.01 | 1.44(1.08–1.91.08.91) | 0.01 | 231(19.1) | 1.05(0.76–1.46.76.46) | 0.75 | 0.94(0.67–1.31.67.31) | 0.70 | 0.96(0.69–1.35.69.35) | 0.83 |
| ABI ≤0.9§ | ||||||||||||||
| Ts1 | NA | NA | NA | NA | NA | NA | NA | 8(2.0) | ref | ref | ref | |||
| Ts2 | NA | NA | NA | NA | NA | NA | NA | 24(1.7) | 0.87(0.39–1.95.39.95) | 0.73 | 0.89(0.39–2.01.39.01) | 0.78 | 0.88(0.39–1.99.39.99) | 0.76 |
| Ts3 | NA | NA | NA | NA | NA | NA | NA | 17(1.4) | 0.73(0.31–1.72.31.72) | 0.48 | 0.77(0.33–1.81.33.81) | 0.55 | 0.79(0.34–1.88.34.88) | 0.60 |
The reference group was defined as the lower tertile of daily sedentary time (Ts1)
Abbreviation: OR odds ratio, CI confidence interval, ABI Ankle-brachial index, NA not applicable
¶Tertile (Ts) ranges of daily sedentary time (hours/day): 0≤Ts1<2, 2≤Ts2<4, Ts3≥4
§Data are odds ratio (95% confidence interval).
∮P-values from binary logistic regression models with daily sedentary time as independent variable.
Model 1: Adjusted for age and sex.
Model 2: model 1 + current smoking status, current drinking status, BMI, hypertension, diabetes, and dyslipidemia.
Model 3: model 2 + systolic blood pressure, HbA1c, LDL-C
Role of physical activity in modulating the impact of sedentary time
Considering that MVPA has been suggested as a potential moderator of the relationship between sedentary behavior and cardiovascular risk, we assessed the association of daily ST with incidence of PVD stratified by tertiles of MVPA (Fig. 1). The cut-off values for MVPA tertiles were 12 and 24 (MET-h/week).
Fig. 1.
The association of daily sedentary time with the risk of polyvascular disease stratified by tertiles of MVPA. A atherosclerotic plaque; B atherosclerotic stenosis. Tertile (Ts) ranges of daily sedentary time (hours/day): 0<Ts1<2. 2≤Ts2<4. TS3>4; Tertile (Ta) ranges of moderate- to vigorous-intensity physical activity (MET-hour/week: 0≤Ta1<12, 12≤Ta2<24, Ta3≥24; 12 MET-hour/week equivalent to about 240 min of moderate-intensity activity per week; 24 MET-hour/week equivalent to about 480 min of moderate-intensity activity per week. The reference category was the group with the highest level of MPA (Ta3) in combination with the lowest tertile of daily sedentary time (Ts1)>2 arterial territories affected with atherosclerosis (atherosclerotic plaque/stenosis). Adjusted by age, sex, current smoking status, current drinking status, BMI, hypertension, diabetes, dyslipidemia, systolic blood pressure, HbA1c, LDL-C (Model3). Abbreviation: OR odds ratio: CI, confidence interval; MET, metabolic equivalent of task
In the stratified analysis for atherosclerotic plaques (Fig. 1A), we observed that prolonged ST was significantly associated with an increased risk of multi-vessel plaques across all MVPA levels. Specifically, after adjusting for confounders (Model 3), participants with high ST (Ts3) had a significantly higher risk compared to those with low ST, even within the highest tertile of MVPA (OR=2.23, 95% CI: 1.22–4.08, p=0.01). Similar significant associations were observed in the medium (Ta2) and low (Ta1) MVPA groups (p < 0.05 for Ts3). These findings suggest that high levels of MVPA may not fully offset the deleterious effects of prolonged sedentary behavior on plaque formation.
Conversely, regarding atherosclerotic stenosis (Fig. 1B), we did not observe a consistent statistically significant association between daily ST and multi-vessel stenosis across the MVPA categories.
Discussion
In this study, we found that daily sedentary time (ST) is significantly associated with the risk of developing multi-vessel atherosclerotic plaques among middle-aged and older community residents. This association remained robust after adjustment for confounders, suggesting that excessive sedentary behavior is significantly associated with PVD burden. Importantly, this association persisted even when potential mediators were included in the model. These findings suggest that sedentary behavior might be an independent risk factor for PVD beyond traditional metabolic pathways, although the underlying mechanisms and causality require further investigation in longitudinal studies. Given the increased cardiovascular risk associated with sedentary behavior [28] major health organizations such as the European Society of Cardiology, the American Heart Association, and the National Heart Foundation of Australia have issued guidelines advocating for behavioral interventions to reduce cardiovascular risk by modifying sedentary behavior and increasing physical activity (PA). However, specific recommendations for sedentary time (ST) thresholds remain undefined [29].
Our findings align with previous research that links sedentary behavior to hypertension, dyslipidemia, and diabetes [6]. Prolonged sedentary periods negatively affect glucose and lipid metabolism, oxidative stress, and inflammatory responses [30], all of which are critical pathways in cardiovascular disease development [31]. A meta-analysis [32] including millions of adult subjects, indicated that device-based ST exceeding 9 hours/day and self-reported ST over 7 hours/day sharply increased the risk of all-cause mortality. Moreover, the overlap between sedentary behavior and polyvascular disease (PVD) risk factors further supports the idea that sedentary behavior can initiate or promote multiple atherogenic mechanisms leading to multi-vessel atherosclerotic plaques.
Interestingly, while we did not find a significant association between daily ST and multi-vessel stenotic lesions in the overall population, our subgroup analysis revealed a crucial nuance. We observed a significant interaction between hypertension and ST (Pinteraction=0.002), indicating that prolonged sedentary time significantly increases the risk of stenosis specifically in hypertensive patients. This finding aligns with the hypothesis that individuals with pre-existing endothelial dysfunction and higher oxidative stress—conditions prevalent in hypertension—may be more susceptible to the vascular detriments of sedentary behavior. The apparent lack of association in the total population might be explained by the fact that adverse cardiovascular events are often influenced more by plaque structure and stability than by the degree of stenosis alone. Nevertheless, our data suggest that for high-risk populations such as those with hypertension, the pro-stenotic effect of sedentary behavior cannot be ignored.
The effects of sedentary behavior vary across different vascular beds. Our study showed that prolonged ST is associated with atherosclerotic plaques in the extracranial segments of the cerebral arteries, renal arteries, and iliofemoral arteries. However, no significant effects were observed in other vascular territories. These findings are supported by recent studies that have indicated a connection between sedentary behavior and adverse cerebrovascular and peripheral arterial outcomes.
Although previous research suggests that moderate- to vigorous-intensity physical activity (MVPA) can mitigate the risks associated with a sedentary lifestyle—potentially by enhancing laminar shear stress and metabolic regulation—our findings indicate that these benefits may not fully offset the deleterious effects of excessive sedentary time. We observed a persistent, significant association between prolonged ST and multi-vessel atherosclerotic plaques even among participants with the highest levels of MVPA. This suggests that sedentary behavior may act as an independent risk factor for atherosclerosis via distinct pathophysiological pathways that are not completely reversible by bouts of exercise, highlighting the importance of reducing sitting time regardless of physical activity levels.
Our study has several strengths. It is based on high-quality data from a well-characterized cohort of community-dwelling older adults in China (PRECISE), designed and conducted rigorously. We accurately assessed atherosclerotic plaque and stenosis in major arteries using CTA and MRI, providing a comprehensive examination of major arteries throughout the body. It is worth noting that our definition of PVD included both non-stenotic plaques and stenosis, allowing us to capture the full spectrum of atherosclerotic burden from early lesions to advanced disease. However, the study has limitations. The use of self-reported methods to assess daily ST, due to participants' limited educational backgrounds, may lead to underestimation. We did not account for the duration and number of sedentary bouts, which may affect behavior. Additionally, ABI is a rough measure for assessing distal arterial lesions in the lower periphery. Finally, the sample size may be slightly insufficient to detect all potential effects.
Future research should focus on establishing standardized quantitative recommendations for ST and exploring the biological mechanisms linking sedentary behavior to PVD. Interventions to reduce ST and increase PA should be prioritized in public health strategies to improve cardiovascular outcomes. Additionally, future studies should consider using objective measures for sedentary behavior and expanding sample sizes to confirm these findings and further elucidate the impact of physical activity on sedentary-related cardiovascular risks.
Conclusion
In this study, daily ST was significantly associated with the risk of multi-vessel atherosclerotic plaques, independent of physical activity levels. Notably, this association persisted even after stratification by moderate- to vigorous-intensity physical activity (MVPA), suggesting that excessive sedentary behavior is an independent risk factor for the development of atherosclerotic plaques across multiple arterial territories. Specifically, prolonged daily ST was linked to a higher risk of atherosclerotic plaques in the extracranial segments of the cerebral arteries and the iliofemoral arteries, as well as an increased incidence of renal artery plaques and stenotic lesions.
These findings underscore the importance of reducing sedentary time in addition to increasing physical activity for optimal vascular health. The ongoing PRECISE study is expected to offer valuable insights into the long-term impacts of sedentary behavior on the progression of vascular lesions and adverse outcomes associated with vascular disease during the four-year follow-up period. Given these results, it is imperative to continue exploring the relationship between sedentary behavior and vascular health, particularly through longitudinal studies and objective measurement techniques.
Supplementary Information
Authors’ contributions
Study design:Jin, Wang and Wei; Drafting: Cao, Li; Statistical analysis: Pan, Cai and Hu; Image analysis:Jing.
Funding
This work was supported by National Natural Science Foundation of China (81971091), Beijing Hospitals Authority Youth Programme (QML20190501), Key Science & Technologies R&D Program of Lishui City (2019ZDYF18), Zhejiang provincial program for the Cultivation of High-level Innovative Health talents and AstraZeneca Investment (China) Co., Ltd.
Data availability
All data generated or analysed during this study are included in this published article and its supplementary information files.
Declarations
Ethics approval and consent to participate
The PRECISE protocol and data collection were approved by the ethics committee of Beijing Tiantan Hospital (IRB approval number: KY2017-010-01) and Lishui Hospital (IRB approval number: 2016–42). All participants signed written informed consent before data collection.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Xiaojing Cao and Shan Li contributed equally to this work.
Contributor Information
Tiemin Wei, Email: lswtm@sina.com.
Zening Jin, Email: ttyyjzn@163.com.
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Associated Data
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Supplementary Materials
Data Availability Statement
All data generated or analysed during this study are included in this published article and its supplementary information files.